Abstract
This work presents a method for creating a mass spectral library containing tandem spectra of identifiable peptide ions in the tryptic digestion of a single protein. Human serum albumin (HSA(1)) was selected for this purpose owing to its ubiquity, high level of characterization and availability of digest data. The underlying experimental data consisted of ∼3000 one-dimensional LC-ESI-MS/MS runs with ion-trap fragmentation. In order to generate a wide range of peptides, studies covered a broad set of instrument and digestion conditions using multiple sources of HSA and trypsin. Computer methods were developed to enable the reliable identification and reference spectrum extraction of all peptide ions identifiable by current sequence search methods. This process made use of both MS2 (tandem) spectra and MS1 (electrospray) data. Identified spectra were generated for 2918 different peptide ions, using a variety of manually-validated filters to ensure spectrum quality and identification reliability. The resulting library was composed of 10% conventional tryptic and 29% semitryptic peptide ions, along with 42% tryptic peptide ions with known or unknown modifications, which included both analytical artifacts and post-translational modifications (PTMs) present in the original HSA. The remaining 19% contained unexpected missed-cleavages or were under/over alkylated. The methods described can be extended to create equivalent spectral libraries for any target protein. Such libraries have a number of applications in addition to their known advantages of speed and sensitivity, including the ready re-identification of known PTMs, rejection of artifact spectra and a means of assessing sample and digestion quality.
Highlights
Shotgun proteomics is a widely used and evolving method for determining the protein composition of a biological mixture [1,2,3]
This paper describes methods for building a tandem mass spectral library capable of characterizing all identifiable peptides in a tryptic digest of a selected protein
It needs to deal with the wide diversity of digestion products, many of which cannot be predicted in advance and whose relative concentrations are likely to depend on complex chemical processes that cannot be fully controlled
Summary
Scores would depend on the “prior probability” [40] that a particular variety of peptide ion would be present in the digest - this is not done by present methods. Filter 1: Peptide Ion Significance—This filter rejects identifications with weak signals that occur rarely It uses two derived values, the median relative abundance, MRAB, and peptide ion identification frequency, PIIF. The PIIF was the fraction of runs that an ion was identified, excluding special cases such as nonalkylated runs These two values were computed separately for LTQ and LTQ Orbitrap data. Based on examination of spectra and findings from the NIST human ion trap library, spectra were rejected when the fraction of the largest 20 fragment ions (excluding neutral loss from the precursor) above the precursor m/z was less than 0.2 for charge 2, 0.3 for charge 3, or 0.36 for charge state higher than 3. This led to improvements in the methods
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
